Qualitative estimation of camera motion parameters from the linear composition of optical flow

Abstract

In this paper, we propose a new method for estimating camera motion parameters based on optical flow models. Camera motion parameters are generated using linear combinations of optical flow models. The proposed method first creates these optical flow models, and then linear decompositions are performed on the input optical flows calculated from adjacent images in the video sequence, which are used to estimate the coefficients of each optical flow model. These coefficients are then applied to the parameters used to create each optical flow model, and the camera motion parameters implied in the adjacent images can be estimated through a linear composition of the weighted parameters. We demonstrated that the proposed method estimates the camera motion parameters accurately and at a low computational cost as well as robust to noise residing in the video sequence being analyzed. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.